{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 02. MultipleParameterTutorial\n",
    "\n",
    "In this tutorial, you will learn how to:\n",
    "\n",
    "* Optimize the Objective Function with Multiple HyperParameters\n",
    "* Define different types of Search Space"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import HyperOpt Library\n",
    "from hyperopt import tpe, hp, fmin\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Declares a objective function to optimize. Unlike last time, we will optimize the function with two Hyperparameters, $x$ and $y$.\n",
    "\n",
    "$$ z = sin\\sqrt{x^2 + y^2} $$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def objective(params):\n",
    "    x, y = params['x'], params['y']\n",
    "    return np.sin(np.sqrt(x**2 + y**2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Just like last time, let's try visualizing it. But unlike last time, there are two Hyperparameters, so we need to visualize them in 3D space."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import cm\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "\n",
    "x = np.linspace(-6, 6, 30)\n",
    "y = np.linspace(-6, 6, 30)\n",
    "x, y = np.meshgrid(x, y)\n",
    "\n",
    "z = objective({'x': x, 'y': y})\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = plt.axes(projection='3d')\n",
    "ax.plot_surface(x, y, z, cmap=cm.coolwarm)\n",
    "\n",
    "ax.set_xlabel('x')\n",
    "ax.set_ylabel('y')\n",
    "ax.set_zlabel('z')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Likewise, let's define the search space. However, this time, you need to define two search spaces($x, y$), so you put each of them in the `dict()`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "space = {\n",
    "    'x': hp.uniform('x', -6, 6),\n",
    "    'y': hp.uniform('y', -6, 6)\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Perfect! Now you can do exactly what you did at BasicTutorial!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100%|██████████| 1000/1000 [00:07<00:00, 127.90trial/s, best loss: -0.9999976342002768]\n",
      "{'x': 4.278018218372159, 'y': 1.97095757186186}\n"
     ]
    }
   ],
   "source": [
    "best = fmin(\n",
    "    fn=objective, # Objective Function to optimize\n",
    "    space=space, # Hyperparameter's Search Space\n",
    "    algo=tpe.suggest, # Optimization algorithm (representative TPE)\n",
    "    max_evals=1000 # Number of optimization attempts\n",
    ")\n",
    "print(best)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define different types of Search Space"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* `hp.randint(label, upper)` searches the integer in the [0, upper) interval.\n",
    "* `hp.choice(label, list)` searches for elements in the list."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100%|██████████| 100/100 [00:00<00:00, 396.61trial/s, best loss: -12.0]\n",
      "{'x1': 2, 'x2': 4}\n"
     ]
    }
   ],
   "source": [
    "def f(params):\n",
    "    x1, x2 = params['x1'], params['x2']\n",
    "    if x1 == 'james':\n",
    "        return -1 * x2\n",
    "    if x1 == 'max':\n",
    "        return 2 * x2\n",
    "    if x1 == 'wansoo':\n",
    "        return -3 * x2\n",
    "\n",
    "search_space = {\n",
    "    'x1': hp.choice('x1', ['james', 'max', 'wansoo']),\n",
    "    'x2': hp.randint('x2', -5, 5)\n",
    "}\n",
    "\n",
    "best = fmin(\n",
    "    fn=f,\n",
    "    space=search_space,\n",
    "    algo=tpe.suggest,\n",
    "    max_evals=100\n",
    ")\n",
    "\n",
    "print(best)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
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   "pygments_lexer": "ipython3",
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